Sentiment lexicon acquisition and expansion relate to the process by which words reflecting sentiment in a text are identified. Identification of sentiments can be very important in textual analysis, Natural Language Processing (NLP), and text mining, as a sentiment may provide a view of or attitude toward a situation, event, or object, and/or reflect feelings or emotions. The task of sentiment lexicon acquisition is typically a labor-intensive and highly manual process. One challenge to automating this process is the problem of sensitivity to the domain of sentiment classification. That is, when classifying textual interactions that originate from different domains using a generic sentiment lexicon the classification accuracy may be poor unless the underlying lexicon used was adapted to the domain. Processes have been developed to identify sentiments in a text. However, these processes are typically manual and very labor intensive. Systems and methods are needed which partially or fully automate the process of sentiment lexicon expansion, which would reduce total cost of operation and increase coverage.